The 3rd Generation Partnership Project (3GPP) and other standardization bodies have long been working on telecommunications systems that provide peak data rates of 100 Mbps and beyond. As one the example, the 3GPP Long Term Evolution (LTE) standard can be mentioned. In LTE, high peak data rates are achieved by sophisticated mechanisms such as link adaptation and Hybrid Automatic Retransmission Request (HARQ) schemes.
In short, link adaptation allows a base station to select modulation and coding parameters individually per user terminal based on the current channel quality. In LTE, link adaption is supported by Orthogonal Frequency Division Multiple Access (OFDMA) in the downlink and Single Carrier FDMA (SC-FDMA) in the uplink. An LTE OFDM downlink signal comprises multiple orthogonal sub-carriers that can be addressed to different user terminals.
HARQ schemes enhance the acknowledgement, retransmission and time-out features of conventional ARQ schemes with Forward Error Correction, FEC, coding (using, for example, so-called Turbo Codes) and with the transmission of error detection information (such as Cyclic Redundancy Check bits). HARQ schemes improve system throughput by combining, rather than discarding, information received via previous erroneous transmission attempts with information received with a current attempt.
FIG. 1 illustrates a block diagram of components of an exemplary OFDM receiver 10 that supports HARQ. The receiver 10 comprises a Fast Fourier Transformer (FFT) 20, a frequency domain equalizer 30, a de-mapper 40 and a channel decoder 50.
An OFDM time domain signal received via a channel is converted by the FFT 20 into the frequency domain to extract the orthogonal sub-carriers. Downstream of the FFT 20 the equalizer 30 individually compensates the channel impact for each sub-carrier in the frequency domain. To this end each sub-carrier is processed based on an estimated channel frequency response. Then, the de-mapper 40 (also referred to as demodulator) reproduces the digital information contained in the output signal of the equalizer 30 by de-mapping points in a constellation diagram into bit sequences. This process is also referred as demodulation and reverses the mapping, or modulation, performed on a transmitter side. The channel decoder 50 decodes the output of the de-mapper 40 and generates sequences of decoded bits as shown in FIG. 1.
During OFDM signal generation a transmitter maps, or modulates, digital information onto sub-carriers for transmission via the channel. Sub-carrier modulation is performed by varying on or both of a phase and an amplitude of a sub-carrier in accordance with the digital information to be transmitted, giving rise to both In-phase (I) and Quadrature (Q) sub-carrier waves.
By way of modulation, binary data are grouped into sequences of i bits that constitute one symbol. Hence, each symbol corresponds to one of 2i possible points, and the total number of points is referred to as a constellation. A constellation can be represented in the form of a constellation diagram in an I/Q plane, wherein the values of I and Q may be interpreted as the real and imaginary parts, respectively.
Now returning to the receiver 10 of FIG. 1, the de-mapper 40 is in charge of de-mapping a point in the constellation diagram into the underlying symbol, or bit sequence. A de-mapping scenario for an exemplary Quadrature Amplitude Modulation (QAM) constellation with 16 points in the I/Q plane (“16-QAM”) and a resulting bit sequence b3b2b1b0 having a length of i=4 is described in Ch. Axell and M. Brogsten, “Efficient WiMAX Receiver Implementation on a Programmable Baseband Processor”, LiTH-ISY-EX-06/3858-SE, Linköping University (2006-10-12), section 7.5.1 (http://www.ep.liu.se/).
FIG. 2 illustrates the 16-QAM de-mapping procedure for the Most Significant Bit (MSB) b3 of the bit sequence b3b2b1b0=00002. This specific bit sequence corresponds to constellation point [I, Q]=[1, 1] in the 16-QAM I/Q plane.
In FIG. 2, the output signal of the equalizer 30 is marked by “X”. As can be seen, the marking “X” does not fully coincide with the constellation point [1, 1] due to channel variations and other imperfections. For this reason a decision procedure is performed by the de-mapper 40 to identify a point in the constellation diagram that corresponds to the marking “X”. This decision procedure is based on repeatedly applying decision boundaries in the constellation diagram. The exemplary decision boundary illustrated in FIG. 2 for MSB b3 is selected to coincide with the Q axis (i.e., an axis defined by I=0). If the received in-phase signal portion is larger than zero (I>0) the transmitted symbol can be assumed to be located in the right half plane in FIG. 2, where all symbols with MSB b3=0 are located. Accordingly, the boundary decision illustrated in FIG. 2 results in b3=0. Similar boundary decisions (but using other decision boundaries) are performed for the remaining bits b2, b1, and b0.
The decision procedure outlined above only provides the bit sequence b3b2b1b0 with no additional information about the reliability, or probability of correctness, of the individual decisions. In other words, the output of the de-mapper 40 provided to the decoder 50 does not permit any conclusions about the closeness of the marking “X” in FIG. 2 to the associated point [1, 1] in the constellation diagram. Evidently, the operation of the decoder 50 would benefit from such probability information. Therefore, Ch. Axell and M. Brogsten suggest adopting the so-called Ramesh algorithm that also provides probability information during the de-mapping process (see sections 7.5.2 and 7.5.3).
The Ramesh algorithm uses decision boundaries as explained above but produces supplemental information about the probability of an individual decision. Specifically, the Ramesh algorithm generates for each decision (i.e., each bit of the bit sequence) an output value in the form of a signed magnitude representative of extrinsic probability information. The sign of the output value is indicative of a bit value 1 or 0, and the magnitude (i.e., the absolute value) is indicative of a distance to the applied decision boundary.
The signed magnitude output by the Ramesh algorithm constitutes extrinsic probability information for the decoder 50. This probability information, which is sometimes also referred to as “soft bit” information, significantly improves the performance of an error correction algorithm and other procedures implemented in the decoder 50.